Construction of a novel immune-related lncRNA signature and its potential to predict the immune status of patients with hepatocellular carcinoma
Autor: | Min Deng, Jia-Bao Lin, Rong-Ce Zhao, Shao-Hua Li, Wen-Ping Lin, Jing-Wen Zou, Wei Wei, Rong-Ping Guo |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Adult
Male Immune-related lncRNA Cancer Research Carcinoma Hepatocellular Adolescent Hepatocellular carcinoma Bioinformatics Datasets as Topic Kaplan-Meier Estimate Risk Assessment Young Adult Predictive Value of Tests Biomarkers Tumor Tumor Microenvironment Genetics Humans RNA-Seq Immune Checkpoint Inhibitors RC254-282 Aged Aged 80 and over Liver Neoplasms Neoplasms. Tumors. Oncology. Including cancer and carcinogens Middle Aged Prognosis Gene Expression Regulation Neoplastic Survival Rate ROC Curve Oncology Drug Resistance Neoplasm Female RNA Long Noncoding Tumor Escape Transcriptome Research Article Follow-Up Studies |
Zdroj: | BMC Cancer, Vol 21, Iss 1, Pp 1-12 (2021) BMC Cancer |
ISSN: | 1471-2407 |
Popis: | Background The accuracy of existing biomarkers for predicting the prognosis of hepatocellular carcinoma (HCC) is not satisfactory. It is necessary to explore biomarkers that can accurately predict the prognosis of HCC. Methods In this study, original transcriptome data were downloaded from The Cancer Genome Atlas (TCGA) database. Immune-related long noncoding ribonucleic acids (irlncRNAs) were identified by coexpression analysis, and differentially expressed irlncRNA (DEirlncRNA) pairs were distinguished by univariate analysis. In addition, the least absolute shrinkage and selection operator (LASSO) penalized regression was modified. Next, the cutoff point was determined based on the area under the curve (AUC) and Akaike information criterion (AIC) values of the 5-year receiver operating characteristic (ROC) curve to establish an optimal model for identifying high-risk and low-risk groups of HCC patients. The model was then reassessed in terms of clinicopathological features, survival rate, tumor-infiltrating immune cells, immunosuppressive markers, and chemotherapy efficacy. Results A total of 1009 pairs of DEirlncRNAs were recognized in this study, 30 of these pairs were included in the Cox regression model for subsequent analysis. After regrouping according to the cutoff point, we could more effectively identify factors such as aggressive clinicopathological features, poor survival outcomes, specific immune cell infiltration status of tumors, high expression level of immunosuppressive biomarkers, and low sensitivity to chemotherapy drugs in HCC patients. Conclusions The nonspecific expression level signature involved with irlncRNAs shows promising clinical value in predicting the prognosis of HCC patients. |
Databáze: | OpenAIRE |
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